Direct Sum Proof Homework: Solve V = im(T) + ker(S)

In summary, the conversation discusses a proof involving the equation V = im(T) + ker(S), which states that the intersection of im(T) and ker(S) is equal to {0} and the sum of im(T) and ker(S) is equal to the space V. The conversation also considers the equations ST = 1v and TS = 1w, and uses this to show that w - TS(w) is in ker(S) and TS(w) is in im(T). The conversation concludes with a possible approach for showing that the sum of im(T) and ker(S) is equal to V.
  • #1
jumbogala
423
4

Homework Statement


Here's the question... it was easier to format it in paint haha:
linalg.jpg


Please note I'll just write + to mean the plus with the circle around it (direct sum). + is just a normal addition.

Homework Equations





The Attempt at a Solution


V = im(T) + ker(S) means that im(T) ∩ ker(S) = {0} and that im(T) + ker(S) = V.

If ST = 1v, then TS = 1w. Thus w = T(v) and v = S(w).
S[w - TS(w)] = S(w) - STS(w) = v - ST(v) = v - S(w) = v -v = 0, therefore it's in ker(S).

Now I'm stuck. I don't know how to use this to do the proof... I think showing the intersection might go:
im(T) ∩ ker(S) = T(v) ∩ w - TS(w) = w ∩ 0 = 0. But I'm not sure.

I have no idea about the im(T) + ker(S) part though.
 
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  • #2
Update: I'm thinking about using

w = (w - TS(w)) + TS(w).

Then w-TS(w) is in ker(S) and TS(w) is in im(T). Although I guess this is not really helpful because this doesn't show that it's equal to the space V...
 

1. What is the purpose of a direct sum proof?

A direct sum proof is used to show that a vector space can be decomposed into two subspaces that have a specific relationship with each other. In this case, we are trying to show that the vector space V can be broken down into the image of a linear transformation T and the kernel of a linear transformation S.

2. What is the difference between the image of a linear transformation and the kernel of a linear transformation?

The image of a linear transformation T is the set of all possible outputs that can be obtained by applying T to the input vector space. On the other hand, the kernel of a linear transformation S is the set of all input vectors that produce an output of 0 when S is applied to them.

3. How do you prove that V = im(T) + ker(S)?

To prove that V = im(T) + ker(S), we need to show that every vector in V can be written as a sum of a vector in im(T) and a vector in ker(S). This can be done by first showing that im(T) and ker(S) are subspaces of V, and then showing that their sum spans V and is linearly independent.

4. What is the significance of the direct sum in this proof?

The direct sum in this proof shows that the two subspaces im(T) and ker(S) are complementary, meaning that they share only the zero vector in common. This allows us to uniquely decompose any vector in V into a sum of a vector in im(T) and a vector in ker(S).

5. Can this proof be applied to any vector space?

Yes, this proof can be applied to any vector space that has a linear transformation T and S defined on it. As long as the vector space V can be decomposed into the image of T and the kernel of S, this proof can be used to show that V is the direct sum of those two subspaces.

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